Method load

tasks/AutoMem/code/memory_layer.py:446–462

Load retriever state from disk

(cls, retriever_cache_file: str, retriever_cache_embeddings_file: str)

            
    @classmethod
    def load(cls, retriever_cache_file: str, retriever_cache_embeddings_file: str):
        """Load retriever state from disk"""
        # Load the pickled state
        with open(retriever_cache_file, 'rb') as f:
            state = pickle.load(f)
            
        # Create new instance
        retriever = cls(model_name=state['model_name'], alpha=state['alpha'])
        retriever.bm25 = state['bm25']
        retriever.corpus = state['corpus']
        retriever.document_ids = state.get('document_ids', {})
        
        # Load embeddings from numpy file if it exists
        if retriever_cache_embeddings_file.exists():
            retriever.embeddings = np.load(retriever_cache_embeddings_file)
            
        return retriever
    
    @classmethod
    def load_from_local_memory(cls, memories: Dict, model_name: str, alpha: float) -> bool: